Retrieval-induced forgetting is the forgetting of memories as a result of retrieving other, similar memories. Although retrieval-induced forgetting has been well characterized behaviorally, its neural mechanism is poorly understood. The proposed research uses electrophysiology in humans to monitor the brain activity that correlates with retrieval-induced forgetting. Pattern classification methods will be used to track the activation of memories during retrieval. The pattern of memory activation that leads to forgetting will be extracted using a subsequent forgetting analysis. Neural network simulations of retrieval-induced forgetting predict a specific pattern of memory activation relative to theta band oscillations. These predictions will be tested through examination of how the activation of the to-be-forgotten memories depends on theta phase. The proposed research will also refine the neural network model of retrieval-induced forgetting, by applying it to a hippocampal architecture, and by using more realistic forms of inhibition. Understanding the precise neural mechanisms that govern retrieval-induced forgetting will help us to gain better control over when forgetting occurs, which - in turn - should help us devise better treatments for Post-Traumatic Stress Disorder (where more forgetting is desirable) and age-related memory disorders (where less forgetting is desirable). [unreadable] [unreadable] [unreadable]